Whole-Genome Tiling Array Analysis of <i>Mycobacterium leprae</i> RNA Reveals High Expression of Pseudogenes and Noncoding Regions
Bibliographic record
Abstract
Whole-genome sequence analysis of Mycobacterium leprae has revealed a limited number of protein-coding genes, with half of the genome composed of pseudogenes and noncoding regions. We previously showed that some M. leprae pseudogenes are transcribed at high levels and that their expression levels change following infection. In order to clarify the RNA expression profile of the M. leprae genome, a tiling array in which overlapping 60-mer probes cover the entire 3.3-Mbp genome was designed. The array was hybridized with M. leprae RNA from the SHR/NCrj-rnu nude rat, and the results were compared to results from an open reading frame array and confirmed by reverse transcription-PCR. RNA expression was detected from genes, pseudogenes, and noncoding regions. The signal intensities obtained from noncoding regions were higher than those from pseudogenes. Expressed noncoding regions include the M. leprae unique repetitive sequence RLEP and other sequences without any homology to known functional noncoding RNAs. Although the biological functions of RNA transcribed from M. leprae pseudogenes and noncoding regions are not known, RNA expression analysis will provide insights into the bacteriological significance of the species. In addition, our study suggests that M. leprae will be a useful model organism for the study of the molecular mechanism underlying the creation of pseudogenes and the role of microRNAs derived from noncoding regions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".